Leveraging dynamic capabilities to drive innovation and enhance business performance: insights from the café industry in Malang City

This study explores the critical role of dynamic capabilities in enhancing business performance among small and medium-sized enterprises (SMEs) in the café sector of Malang City, Indonesia. Specifically, it examines how dynamic capabilities influence both explorative and exploitative innovations and how these innovations, in turn, affect business performance. Using a quantitative approach, data were collected from 110 café owners through structured questionnaires. The results indicate that dynamic capabilities significantly impact both explorative and exploitative innovations. Explorative innovation, which involves the development of new products and the exploration of new markets, was found to have a substantial positive effect on business performance. Conversely, exploitative innovation, which focuses on refining and improving existing products and processes, showed a positive but less pronounced impact. The findings underscore the importance of dynamic capabilities in fostering innovation and improving business performance in a competitive environment. This study offers practical insights for café owners and entrepreneurs in the food and beverage sector, highlighting the need for continuous development of dynamic capabilities and a balanced approach to innovation. Future research is encouraged to expand on these findings by exploring additional factors and utilizing longitudinal data to capture the evolving nature of these relationships.


Introduction
Small and Medium Enterprises (SMEs) in Indonesia serve as the backbone of the national economy, playing a crucial role in fostering economic growth, reducing unemployment, and combating poverty.Recognized by the Indonesian government as vital to national development, SMEs significantly contribute to job creation and societal welfare.According to the Ministry of Economic Affairs, SMEs account for nearly 61% of the country's Gross Domestic Product (GDP) and employ approximately 97% of the workforce.This substantial contribution highlights not only their support for the local economy by providing goods and services but also their role in maintaining social stability through more equitable income distribution.
In the diverse economic landscape of Indonesia, the food and beverage sector stands out, with over 1.5 million SMEs operating within it, as reported by the Central Bureau of Statistics (BPS) in 2022.This sector forms the economic backbone of many local communities and serves as a source of innovation and sustainability.From street vendors to large-scale food producers, these enterprises contribute significantly by meeting local consumption needs and driving economic activity through job creation and skill development.The increasing importance of this sector is further underscored by its substantial contribution to the national GDP, particularly in the second quarter of 2022, where it generated 302.28 trillion Rupiah (BPS, 2022).
The café industry in Malang, a city renowned for its vibrant food and beverage sector, exemplifies both the opportunities and challenges faced by SMEs in this sector.Local government initiatives, such as the 'Kemis Mbois' program, have successfully supported these businesses, earning accolades like the 'Innovation Building the Nation 2023' award in the SME Empowerment category (Aminudin, 2023).Despite these efforts, the café sector in Malang is highly competitive, with a notable increase in new entrants, which, while stimulating economic activity, also raises concerns about sustainability and business performance (Novrian, 2024).The high competition has led to a significant number of cafés struggling to survive, emphasizing the need for effective strategies to ensure business sustainability.
To navigate this competitive landscape, the theoretical frameworks of dynamic capabilities and the Resource-Based View (RBV) offer valuable insights.RBV posits that a firm's competitive advantage stems from its ability to develop and manage unique, inimitable resources, including innovation and human resource capacity (David et al., 2023).Innovation allows firms to create products and services distinct from their competitors, making them more attractive to consumers and capable of meeting everchanging market needs.Concurrently, strong human resource capacity ensures that firms have the skilled and knowledgeable workforce necessary to implement innovation strategies effectively (Helfat, 2017).
Achieving an ambidextrous strategy, which balances exploratory and exploitative innovations, is critical for maintaining business performance and ensuring long-term sustainability (Zakrzewska-Bielawska, 2021).Exploration involves seeking and developing new opportunities, requiring innovation and risk-taking, while exploitation focuses on utilizing and optimizing existing resources to enhance efficiency and effectiveness.For this, robust dynamic capabilities are essential, enabling firms to integrate, build, and reconfigure internal and external competencies to address rapidly changing environments (Berszinn-Cordes, 2013).Dynamic capabilities encompass the capacity to proactively and responsively renovate and transform resources and capabilities in reaction to fast and unpredictable environmental changes (Farzaneh et al., 2022;Fitriati et al., 2020).
However, previous studies present inconsistent findings regarding the impact of dynamic capabilities on innovation and business performance.For instance, Abbas et al. (2019) and Fitriati et al. (2020) highlight the positive impact of dynamic capabilities on business performance and innovation, while Eikelenboom & De Jong (2019) and Sukaris et al. (2021) report non-significant effects.This research aims to address these inconsistencies by examining the mediating role of exploratory and exploitative innovations in the relationship between dynamic capabilities and business performance within Malang's café sector.
By analyzing the impact of dynamic capabilities on the business performance of cafés in Malang, this study seeks to assess how these capabilities influence exploratory and exploitative innovation, and examine the relationships between these types of innovation and business performance.The findings will provide empirical evidence on the importance of balancing exploration and exploitation to enhance business performance.Furthermore, the insights gained will offer practical guidance for policymakers and business owners to develop strategies that leverage dynamic capabilities and innovation for sustainable business growth, thereby addressing the research gap and contributing to the literature on dynamic capabilities and innovation in SMEs.
The significant role of SMEs, especially in the food and beverage sector, underscores the importance of strategic innovation and robust dynamic capabilities for sustaining business performance amidst competitive pressures.This study aims to provide a comprehensive understanding of how dynamic capabilities and innovation can drive business success in the highly competitive café industry of Malang.

Resource-Based View Theory (RBV)
The Resource-Based View (RBV) theory posits that a firm's sustainable competitive advantage is derived from its ability to assemble and exploit an appropriate combination of resources.These resources must be valuable, rare, inimitable, and non-substitutable (VRIN) to provide long-term advantages (David et al., 2023).In the context of SMEs, particularly in the food and beverage sector, resources such as innovative capabilities, skilled human resources, and unique organizational processes can be pivotal.The RBV emphasizes internal resource management over external market conditions, arguing that internal capabilities can lead to a sustainable competitive edge (David et al., 2023;Rothärmel, 2024).

Organizational Capabilities
Organizational capabilities refer to a firm's ability to manage and orchestrate resources effectively to achieve desired outcomes.These capabilities are often categorized into operational capabilities, which deal with the efficient use of resources, and dynamic capabilities, which focus on the firm's ability to renew and recreate its strategic assets to meet changing environments (Helfat, 2017).Organizational capabilities are essential for SMEs to adapt to market dynamics and competitive pressures.They encompass skills, routines, and competencies that firms develop over time to manage resources strategically and operationally (Helfat, 2017).

Business Performance
Business performance refers to how well an organization achieves its goals and objectives, often measured through financial metrics such as profitability, revenue growth, and return on investment, as well as non-financial metrics like customer satisfaction, market share, and innovation outcomes (Estrada-Torres et al., 2021).For SMEs, especially those in competitive sectors like food and beverage, maintaining high business performance is critical for survival and growth.Effective management of organizational resources and capabilities is key to enhancing business performance (Kurniasari et al., 2021).

Dynamic Capabilities
Dynamic capabilities refer to the firm's abilities to integrate, build, and reconfigure internal and external competencies to address rapidly changing environments (Helfat, 2017).These capabilities enable firms to sense opportunities and threats, seize opportunities, and maintain competitiveness by transforming their resource base (Berszinn-Cordes, 2013).They are crucial for fostering both exploratory and exploitative innovation, which in turn directly impacts business performance.
In strategic management theory, dynamic capabilities allow organizations to achieve and maintain a competitive advantage in dynamic and competitive markets (Helfat, 2017).Within organizational contexts, they refer to a firm's capacity to proactively and responsively renovate and transform its resources and capabilities in reaction to fast and unpredictable environmental changes (Berszinn-Cordes, 2013).Such capabilities are essential for driving explorative innovation, where firms seek new knowledge, develop novel products or services, and enter new markets (Farzaneh et al., 2022).Explorative innovation is often viewed as radical, allowing firms to explore uncharted territories with a focus on long-term value creation through new ideas and concepts (Veiga et al., 2024).
In addition, dynamic capabilities significantly enhance exploitative innovation, which focuses on utilizing and improving existing resources, processes, and capabilities (Veiga et al., 2024).Exploitative innovation involves incremental improvements aimed at increasing operational efficiency and effectiveness (Lu et al., 2023).This type of innovation emphasizes short-term value creation and is considered lower risk, as it relies on known and tested technologies and processes (Lu et al., 2023).Effective organizational adaptation to competitive environmental changes, particularly those affecting consumer behavior patterns, heavily relies on exploitative innovation.
Several studies, including those by Abbas et al. (2019) and Fitriati et al. (2020), have demonstrated that dynamic capabilities positively affect business performance by fostering both explorative and exploitative innovations.By enabling firms to adapt to environmental changes, capitalize on emerging opportunities, and mitigate threats, dynamic capabilities ensure that firms remain competitive and achieve sustained growth (Fitriati et al., 2020).Thus, several hypotheses can be made from this explanation.H1: Dynamic Capabilities Have a Significant Effect on Explorative Innovation.

H2: Dynamic Capabilities Have a Significant Effect on Exploitative Innovation.
H3: Dynamic Capabilities Have a Significant Effect on Business Performance.

Explorative Innovation
Explorative innovation involves the development of new products, services, or processes that are fundamentally different from the firm's existing offerings.This type of innovation requires a willingness to take risks and invest in uncertain outcomes (Farzaneh et al., 2022).Explorative innovation is crucial for long-term success as it allows firms to enter new markets, create new value propositions, and respond to disruptive changes in the industry.
By enabling firms to differentiate themselves from competitors, attract new customers, and create new revenue streams, explorative innovation significantly impacts business performance.Studies such as those by Chua et al. (2024), Moreira et al. (2022), andSarfo et al. (2024) indicate that explorative innovation enhances business performance by driving the development of new products and services, thereby creating a competitive edge.However, some studies like Ngo et al. (2019) suggest that the relationship between explorative innovation and business performance can be context-specific.Therefore, a hypothesis can be formulated based on these insights.

H4:
Explorative Innovation Has a Significant Effect on Business Performance.

Exploitative Innovation
Exploitative innovation focuses on refining and improving existing products, services, or processes.It involves leveraging current capabilities to enhance efficiency, reduce costs, and improve quality (Moreira et al., 2022).Exploitative innovation is essential for short-term performance as it maximizes the value derived from existing resources and capabilities.
Enhancing operational efficiency, product quality, and customer satisfaction, exploitative innovation plays a critical role in maintaining and enhancing business performance.Studies by Chua et al. (2024), Moreira et al. (2022), andSingh et al. (2024) suggest that exploitative innovation is pivotal for optimizing existing processes and resources, thereby supporting business performance.However, as noted by Ngo et al. (2019), the impact of exploitative innovation on business performance can vary, indicating a need for further research to fully understand this relationship.Thus, another hypothesis can be made based on these explanations.

H5:
Exploitative Innovation Has a Significant Effect on Business Performance.

Sampling and Data Collection
The population of this research comprises all micro, small, and medium enterprises (MSMEs) that operate cafés in Malang City.Sekaran & Bougie (2020) defines population as the whole collection of entities being investigated, including people, animals, plants, and phenomena.Sampling, as defined by Creswell & Creswell (2018), is the process of choosing a subset of the population that has certain qualities.The sample size is selected according to expert guidelines for assessing latent variables, which suggests a range of 5 to 10 times the number of manifest variables (Hair et al., 2022).The survey consisted of 15 questionnaire questions so the minimum sample size for this study is 75 responden.This research collected sample of 110 café owners in Malang City who have been operating for at least one year till 2023.This study employs non-probability purposive sampling, a technique that involves selecting participants based on specific criteria that are pertinent to the research (Sekaran & Bougie, 2020).Table 1 show the characteristics of respondent collected in this study The analysis results shown in Table 5.1 indicate that a considerable share of café owners in Malang City are males, who dominate the industry in comparison to female.The majority of café proprietors fall between the age bracket of 26-40 years, suggesting that the sector is mostly overseen by energetic people who are receptive to change and innovation.The majority of cafés operate on a large scale, with a significant number of them employing over 10 staff members.This demonstrates their ability to provide a high level of service and maintain a strong operating framework.Regarding revenue, the majority of cafés in Malang City reported monthly turnovers over IDR 100 million, indicating a robust and attractive development potential in the café business.Based on Table 1, Café owners tend to use offline marketing methods, although some also utilize social media to expand their audience.In general, the data indicates that café proprietors in Malang City are mostly young, creative males, overseeing businesses of considerable magnitude and with promising commercial outlooks.

Questionnaire and Measurement
The data for this study was collected through questionnaires, a common method in quantitative research where respondents answer a series of structured questions (Brace & Bolton, 2022).The questionnaire, which was distributed through Google Forms, included statements related to dynamic capabilities, explorative innovation, exploitative innovation, and MSME business performance.The measurement of dynamic capability variables is obtained through research (Martins, 2023) which consists of several indicators, namely, sensing, seizing, and transforming.Measurement of exploitative innovation variables is obtained through the source (Cho et al., 2020) which consists of product development, efficiency of existing business processes, cost reduction, and increasing customer satisfaction.Measurements of explorative innovation variables are obtained through research conducted by (Cho et al., 2020) which consists of indicators of new product development, new segment exploration, new technology adoption, and new business opportunities.Business performance measurements are obtained through research conducted by (Martins, 2023) with constituent indicators, namely market share, sales growth, profitability, and operational efficiency.A Likert scale, which ranges from "strongly disagree" (1) to "strongly agree" (5), was used to measure responses.The Likert scale was chosen for its simplicity and effectiveness in capturing respondents' attitudes towards social phenomena (Brace & Bolton, 2022).

Data Analysis
Data analysis in this study involved descriptive statistical analysis and Partial Least Squares Structural Equation Modeling (PLS-SEM).Descriptive statistics summarize the main features of a dataset, providing measures such as mean, median, mode, standard deviation, and range (Mishra et al., 2019).PLS-SEM is used to examine the relationships between latent variables, which are abstract concepts that cannot be observed directly and require measurement indicators (Merkle et al., 2019).PLS-SEM analysis follows five stages: model specification, which defines the research model and the relationship between latent variables and observed indicators (Hair et al., 2022).

Findings Descriptive Statistics
Descriptive Statistics is used to elucidate the responses given by respondents by providing the mean score on the 5-point Likert scale and the standard deviation of the response scores.This study incorporates descriptive statistics, which include the examination of relationships among the research variables.The descriptive statistics and correlation results presented in the table indicate that dynamic capability (mean = 4.298, SD = 0.514) and explorative innovation (mean = 4.602, SD = 0.579) are relatively high among the respondents, suggesting a strong focus on adaptability and innovation within the cafes.Exploitative innovation (mean = 4.236, SD = 0.760) and business performance (mean = 4.084, SD = 0.827) also show substantial values, indicating efficient utilization of existing resources and overall positive business outcomes.The correlation analysis reveals that dynamic capability has a moderate positive correlation with explorative innovation (r = 0.316), exploitative innovation (r = 0.544), and business performance (r = 0.539), highlighting its significant role in fostering innovation and enhancing business results.Explorative innovation, while positively correlated with exploitative innovation (r = 0.391) and business performance (r = 0.286), shows a stronger link with exploitative practices.Exploitative innovation itself has a moderate positive correlation with business performance (r = 0.376), underscoring its contribution to achieving favorable business outcomes.

Partial Least Square (PLS-SEM)
The purpose of using Partial Least Squares Structural Equation Modeling (PLS-SEM) in this study is to evaluate the validity and reliability of the research instruments, as well as to test the hypotheses about the relationships between variables.Figure 1 presents the results of a Partial Least Squares Structural Equation Modeling (PLS-SEM) study conducted using the WarpPLS 8.0 program.

Figure 1: PLS-SEM Analysis Result
Figure 1 displays the outer loading, which represents the relationship between the measurement items and their latent variables, as well as the path coefficient, which represents the association between variables.

Outer Model Evaluation
The outer model is evaluated to see whether the manifest variables effectively and consistently measure the latent variables being researched in this research.According to Hair et al. (2022), the reflective construct model includes three evaluations: 1) convergent validity, 2) discriminant validity, and 3) internal consistency (reliability).Convergent validity measures the accuracy with which the measuring items describe the construct variables.According to some statisticians, an indicator may be considered credible if its outer loading value exceeds 0.70 (Hair, et.al, 2022).Hair et al. (2022) stated that items with an outer loading below 0.4 should be excluded from the subsequent steps in PLS analysis.However, items with outer loading between 0.4 and 0.7 can be included in constructs if the resulting variable constructs demonstrate satisfactory convergent validity, indicated by an average variance extracted of at least 0.5.Simultaneously, the assessment of internal consistency (reliability) is conducted to verify that the variable constructs in this research are sufficiently trustworthy for empirical measurement of the phenomena.During internal consistency testing, the value of composite reliability (CR) is assessed.A measurement item is considered trustworthy if its composite reliability exceeds 0.70, as stated by Hair et al. (2022).Table 3 displays the outer loading value, average variance extracted (AVE) value, and composite reliability (CR) for each variable.The results of the convergent validity assessment, as shown in Table 5.7, demonstrate that the AVE value for each variable exceeds 0.5.This indicates that all latent variables possess valid indicators.The findings obtained from the AVE analysis align with the results from the outer loading analysis.In the outer loading analysis, no indicators have a loading value below 0.4.Items with loading values between 0.4 and 0.7 are preserved based on the recommendation of Hair et al. (2022) because they meet the criteria for simultaneous convergent validity using AVE.The assessment findings indicate that every variable in this research has a composite reliability value over 0.7, indicating that each variable demonstrates strong internal consistency.
Finally, discriminant validity demonstrates that each variable's items are unique and can only represent that variable.The assessment of discriminant validity is performed by examining the HTMT ratio derived from PLS-SEM analysis using the WarpPLS 8.0 program.Discriminant validity is said to be attained when the HTMT ratio is less than 0.9.The findings of the discriminant validity evaluation, using the HTMT ratio, are shown in Table 4. Based on the evaluation results in Table 4, it is found that the HTMT value in all relationships between variables in this study is below 0.9, so it can be stated that based on the HTMT ratio criteria, discriminant validity has been achieved.As a result of the evaluation of the outer model, it is known that all measurement items are valid and reliable, allowing them to be used to evaluate the research hypothesis.

Inner Model Evaluation
The inner model evaluation in this study is the second stage after evaluating the measurement model (outer model), at the structural model evaluation stage, the relationship between variables will be tested according to the research hypothesis and an evaluation of the goodness of fit model will be carried out.Inner model evaluation consists of five parts, namely: 1) Evaluation of the path coefficient (research hypothesis); 2) Evaluation of the coefficient of determination (R 2 ); 3) Predictive Relevance Assessment (Q 2 ); 4) Effect Size Assessment (f 2 ); 5) Model fit assessment.
Path coefficient evaluation involves examining the path coefficient (β) and p-value to determine the significance of the relationship between variables.The coefficient (R 2 )) is used to assess the degree to which the model can elucidate the research model.Meanwhile, predictive relevance (Q 2 ) show the accuracy of the model, positive Q 2 suggest that the model has good predictive ability.The effect size (f 2 ) is used to quantify the extent of the independent variable's impact on the dependent variable.Cohen (2003) categorizes the strong influence of independent variables based on their effect size.Effect sizes below 0.02 are considered to have no calculable effect from the independent variable.Effect sizes between 0.02 and 0.15 are classified as small effects, while effect sizes between 0.15 and 0.35 are categorized as medium effects.Effect sizes greater than 0.35 are classified as large effects.Table 5 displays the aggregate interior model evaluation results.The findings in Table 5 reveal that Dynamic capability also has a significant positive impact on both explorative and exploitative innovations.The path coefficient (β) for the influence of dynamic capability on explorative innovation is 0.536, with a p-value less than 0.001, and an effect size (f 2 ) of 0.301, indicating a strong influence.This means that higher dynamic capability encourages cafe owners to engage in explorative innovation activities, such as developing new menus and seeking new customer segments.Similarly, the path coefficient (β) for the effect of dynamic capability on exploitative innovation is 0.343, with a p-value less than 0.001, and an effect size (f 2 ) of 0.111, denoting a small to medium effect.This indicates that dynamic capability also helps cafe owners enhance their existing products and services, although the impact is less strong compared to explorative innovation.Thus H1 and H2 supported by analysis result.
The analysis result show dynamic capability also significantly influences business performance among cafe owners in Malang City.The path coefficient (β) for this relationship is 0.417, with a p-value less than 0.001, indicating a highly significant effect.Additionally, the effect size (f 2 ) is 0.222, suggesting a medium effect.This result implies that the better the dynamic capability, the more likely it is that business performance will improve.Therefore, the analysis result support H3 in this research.
Furthermore, the results support H4 in this study that demonstrate explorative innovation significantly impacts business performance.
The path coefficient (β) for this relationship is 0.241, with a p-value of 0.004, and an effect size (f 2 ) of 0.105, suggesting a small effect.This indicates that while explorative innovation contributes positively to business performance, its effect is relatively modest.
On the other hand, the hypothesis that exploitative innovation influences business performance (H5) was not supported.The path coefficient (β) for this relationship is 0.064, with a p-value of 0.249, which is above the 5% significance level, and an effect size (f 2 ) of 0.022, indicating a very small effect.This confirms that exploitative innovation does not significantly affect business performance in this context.
The R values for the endogenous variables indicate the proportion of variance explained by the model.For business performance, the R 2 is 0.111, meaning that 11.1% of the variance is explained by dynamic capability, explorative innovation, and exploitative innovation.For explorative innovation, the R2 is 0.349, indicating that 34.9% of the variance is explained by dynamic capability.
For exploitative innovation, the R 2 is 0.301, indicating that 30.1% of the variance is explained by dynamic capability.Additionally, the predictive relevance (Q 2 ) values are all positive, suggesting that the model has good predictive accuracy for the endogenous variables.These findings collectively validate the structural model, confirming the significant roles of dynamic capability in driving both explorative and exploitative innovations, which subsequently influence business performance, albeit to varying extents.
The assessment of model fit, according to Kock (2014), involves several criteria to evaluate the goodness of fit for a structural model in Partial Least Square (PLS) analysis using WarpPLS.The results of the PLS analysis for this study, as presented in Table 6, show that the structural model meets these criteria, indicating a satisfactory model fit

Discussion
This study underscores the vital importance of dynamic capabilities in enhancing the business performance of SMEs, particularly in the café industry of Malang City.Dynamic capabilities, which encompass the ability to sense market opportunities, seize them, and transform the organization accordingly, are pivotal for businesses operating in rapidly changing environments.These capabilities allow firms to not only respond to but also anticipate changes, enabling them to remain competitive and achieve superior performance.
The findings align with the Resource-Based View (RBV) and Organizational Capabilities Theory, which posit that the effective utilization of resources and capabilities leads to innovation and competitive advantage.In this context, dynamic capabilities facilitate the identification of new opportunities and the development of innovative products or services that meet evolving customer needs.This study supports these theoretical frameworks by demonstrating that SMEs with robust dynamic capabilities tend to perform better.
Explorative innovation, driven by dynamic capabilities, is crucial for businesses seeking to venture into new markets or develop new product lines.This type of innovation involves significant risk and uncertainty but offers substantial rewards by enabling firms to differentiate themselves from competitors and address unmet customer needs.The study's findings suggest that café owners who actively engage in explorative innovation are better equipped to adapt to market shifts and enhance their business performance.This is consistent with research by Farzaneh et al. (2022), who found that dynamic capabilities positively impact ambidextrous innovation, including explorative innovation.Similarly, Fitriati et al. (2020) showed that dynamic capabilities significantly influence innovation in Indonesian SMEs, emphasizing the role of explorative innovation in driving business success.
On the other hand, exploitative innovation, which focuses on refining and improving existing products or services, is essential for maintaining operational efficiency and quality.While exploitative innovation is critical for sustaining day-to-day business operations, the study indicates that it may not be sufficient on its own to drive significant improvements in business performance within the highly competitive café industry of Malang.This finding highlights the need for a balanced approach that incorporates both explorative and exploitative innovations to achieve optimal business outcomes.This result is supported by Farzaneh et al. (2022) but contrasts with Gonzalez (2022), who found that not all dimensions of dynamic capabilities significantly impact exploitative innovation.Moreover, Taghizadeh et al. (2023) found that some dynamic capability dimensions, such as learning, integrating, and coordinating, significantly influence sustainable innovation performance, though sensing did not.
Descriptive analysis of the respondents' characteristics reveals that most café owners in Malang are well-educated and have substantial industry experience.This background likely contributes to their ability to develop and leverage dynamic capabilities effectively.Furthermore, many café owners actively use social media and digital platforms for marketing, which enhances their ability to quickly detect and respond to market trends.This agility is a key component of dynamic capabilities, enabling businesses to stay ahead of competitors and meet changing customer expectations.
The study also highlights the importance of innovation in mediating the relationship between dynamic capabilities and business performance.Innovations, whether explorative or exploitative, serve as the mechanisms through which dynamic capabilities translate into improved business outcomes.Café owners who excel in innovation are likely to see greater benefits from their dynamic capabilities, reinforcing the need for continuous improvement and adaptation.This aligns with findings by Chua et al. (2024) and Moreira et al. (2022), which emphasize the role of digital resources and explorative innovation in enhancing business performance.
Practical implications of these findings suggest several strategies for café owners and entrepreneurs in the food and beverage sector.Firstly, there is a need to prioritize the development of dynamic capabilities through ongoing education and training.Attending industry workshops, engaging in professional development, and staying updated with the latest market trends can help business owners enhance their capabilities.Secondly, leveraging technology and social media is crucial for detecting market changes and engaging with customers effectively.Digital tools can provide valuable insights into consumer behavior, preferences, and emerging trends, enabling businesses to respond promptly and strategically.
Additionally, café owners should foster a culture of innovation within their organizations.Encouraging creativity, experimentation, and risk-taking can lead to the development of new products and services that resonate with customers.It is also essential to strike a balance between explorative and exploitative innovations.While explorative innovation can open new avenues for growth, exploitative innovation ensures that existing operations are efficient and effective.The findings also suggest that collaboration and networking can enhance dynamic capabilities.Building relationships with other businesses, industry experts, and academic institutions can provide access to new knowledge, resources, and opportunities.Such collaborations can help café owners stay ahead of industry trends and adopt best practices.
This study emphasizes the critical role of dynamic capabilities in driving business performance in the café industry.Café owners who can sense and seize market opportunities, coupled with the ability to innovate, are well-positioned to succeed in a competitive environment.By investing in the development of dynamic capabilities and fostering a culture of innovation, café owners can enhance their business performance and achieve sustainable growth.These strategies are essential for navigating the complexities of today's market and ensuring long-term success.

Conclusions
This study has demonstrated the critical role of dynamic capabilities in enhancing business performance within the café sector in Malang City.The research highlights that dynamic capabilities, which include the abilities to sense, seize, and transform market opportunities, significantly impact both explorative and exploitative innovations.These innovations, in turn, play a crucial role in improving business performance.
Explorative innovation, which involves developing new products and entering new markets, was found to have a strong positive effect on business performance.This type of innovation helps businesses adapt to market changes and create new value for customers.Conversely, while exploitative innovation, focusing on refining and improving existing products and processes, also contributes positively to business performance, its impact is less pronounced than that of explorative innovation.This suggests that while maintaining operational efficiency and quality through exploitative innovation is important, it may not drive significant growth in highly competitive markets.
The study further reveals that dynamic capabilities have a direct positive influence on business performance, underscoring their importance in enabling SMEs to thrive in dynamic environments.Effective management and utilization of these capabilities are vital for achieving sustainable competitive advantage.
From a practical perspective, the findings suggest several strategies for café owners and entrepreneurs.Continuous investment in the development of dynamic capabilities through education, training, and professional development is essential.Leveraging technology and social media to stay attuned to market changes can provide a competitive edge.Additionally, fostering a culture of innovation that balances both explorative and exploitative practices can help businesses achieve both short-term efficiency and long-term growth.
In conclusion, the research underscores the importance of dynamic capabilities and innovation in enhancing business performance in Malang City's café sector.By focusing on both explorative and exploitative innovations, café owners can better navigate competitive market dynamics and achieve sustainable growth.Future research could expand the scope of this study by exploring additional factors influencing business performance and incorporating longitudinal data to capture the dynamic nature of these relationships over time.

Table 2 :
Table 2 show Descriptive statistics of respondent responde and correlation between variables Descriptive Statistics of Respondent Answer

Table 3 :
Convergent Validity and Internal Consistency Evaluation Result

Table 4 :
Discriminant Validity Evaluation Result

Table 5 :
Inner Model Evaluation Result Table4.5 lists these criteria, including Average R-squared (ARS) with a cutoff p-value of ≤ 0.05, Average block Variance Inflation Factor (AVIF) which is acceptable if ≤ 5.0 and ideally ≤ 3.3, Average Full Collinearity Variance Inflation Factor (AFVIF), Tennenhaus Goodness of Fit (TGoF) with a threshold of ≥ 0.36, Sympson's Paradox Ratio (SPR) which is acceptable if ≥ 0.7 and ideally equal to 1, and Statistical Suppression Ratio (SSR).The model is considered to have a good fit if at least one of these criteria is met.

Table 6 :
Model Fit Evaluation Result